Everything on building AI agents, newest first. Looking for the deep dives? Start with the guides.
Anthropic's Applied AI team reveals how to design tools that agents can actually use effectively. Learn the five production-tested principles for building agent tools, with a complete implementation of Cameron AI's expense tracking system.
Learn Anthropic’s production-tested playbook for prompting AI agents like Claude Code. We distill their principles, heuristics, and eval strategies into a practical guide you can use to build reliable, tool-using agents for the real world.
Learn how to build a production-ready fullstack AI agent with Next.js and LangGraph.js. This guide covers Model Context Protocol integration for dynamic tool loading, human-in-the-loop approval workflows, and real-time streaming with React Query.
Learn how to publish your MCP server to the official Model Context Protocol registry with step-by-step instructions and real-world examples.
Explore effective strategies for summarizing message history in AI agents, ensuring they retain crucial context and information.
Side-by-side comparison of LangChain and LangGraph in Python vs TypeScript/JavaScript—APIs, agent patterns, ecosystem maturity, deployment, adoption stats, and practical guidance on when to choose each.